#Google

Firefox’s Smart Window adds AI form filling and webpage monitoring

Mozilla is updating Firefox's AI-powered Smart Window with a feature that fills online forms using information from your open tabs, such as an online portfolio or LinkedIn page, and shares source-page data with Google's Gemini 3.1 Flash Lite. Users can also type "/watch" in the Smart Window chat to have Firefox check specified webpages daily or weekly for sales, job listings and other updates, notifying them when a change is detected. Both features are rolling out to the Smart Window beta on desktop in the US and Canada, with other countries to follow in the "coming months."

Genie 4: A new generation of world simulation

Google announced Genie 4, a natively multimodal world model that generates photorealistic, real-time interactive simulations with native audio, including ambient sound and interactive dialogue, and builds on Gemini models for reasoning and coherence. It is rolling out as a research preview to trusted testers, with plans to reach Google AI Ultra subscribers in Project Genie and early access partners via the Gemini API and Google AI Studio. Google notes limitations such as drift in visual details and object permanence over longer sessions, and says all generated video and audio include SynthID watermarking.

Fast, reliable A2UI, with swappable inference formats

A2UI now supports swappable inference formats, with A2UI Express as the new default that requires up to 3x fewer tokens than Direct JSON and can cut latency by up to 3x, while decision models like Jev can reduce latency by up to 80x for layouts defined in advance. Express is available in the Python agent SDK (a2ui-agent-sdk 0.9.0), the TypeScript agent SDK (@a2ui/agent) and the Dart SDK (a2ui_agent 0.0.1-wip004), and the SDK compiles the model's reply into validated A2UI messages. The post also describes the Apparite (jev2ui) example, where Jev answers layout questions and code builds the component tree, with screens complete in 0.8 to 1.7 s across 11 prompts in a small first-look sample.

Can AI draw San Francisco from memory?

VOYGR tested six chat models from Anthropic, OpenAI and Google on 41,526 San Francisco coordinates, asking what is at each point from memory with no maps or internet, and checked every answer against OpenStreetMap. At a point every 100 m, Gemini 4 Argon, GPT-6.1 Sol and GPT-6 Astra tied at 86% correct on water, park or everything else, against 61% for answering "not water, not park" everywhere, while on a 500 x 500 m Marina block the best street score was 0.32 versus 0.23 for shuffled answers. The authors conclude models capture the coastline and large parks but not street grids, and recommend a geocoder rather than model memory for reverse geocoding.

Meta AI director Rohit Patel leaves to take on Microsoft Office and Google Workspace

TechCrunch reports that Rohit Patel, a former director at Meta Superintelligence Labs, has left Meta after eight years to launch Ndoc, an AI-native workspace pitched as a replacement for Microsoft Office and Google Workspace. Ndoc combines a Stage tab for presentations and dashboards, a Narrative tab for analyses and citations, and a Model tab housing datasets and Python scripts, and is built on a mixture of open source models. Patel plans to open-source the ".ndoc.html" export format, and Ndoc is now running an enterprise pilot with a limited alpha and a beta planned for the coming weeks.

Former Deepmind researcher thinks AlphaGo's playbook can cure AI hallucinations

Former Deepmind researcher Thore Graepel founded Metis Reasoning, which proposes applying AlphaGo's approach of pairing neural networks with systematic search to general reasoning, using an explicit "knowledge ledger" that records what is known and checks new entries against evidence. Metis says the setup should produce fewer hallucinations and knowledge that can be changed without retraining, though the white paper describes only a research program with no working system or benchmarks. Graepel, who worked on AlphaGo, AlphaZero and MuZero, is reportedly raising a low tens-of-millions round for Metis.

Wikipedia's Cleanup of AI-Generated Content

Ellia Lebleu, a founding member of the volunteer WikiProject AI Cleanup launched in 2023, describes how early AI writing was betrayed by clichés like "stands as a testament" while 2025-era signs are subtler and more structural, and she says fake or misleading citations have become a major worry. She estimates, using Pangram detection with no false positives on pre-ChatGPT content, that roughly 20 percent of new articles and drafts were flagged as AI-generated in late 2025, falling to 15 or 16 percent in early 2026, though it is unclear whether policy or stronger models explain the drop. She discusses AI tools used against AI content, Wikipedia's human-written identity, and possible futures including attribution frameworks and reader contributions through AI models.

AI is ruining haunted houses

The author, who has run a home haunted attraction since 2005, describes encountering low-quality AI art, including an image with the Gemini diamond logo, at his first haunt of the year. He argues AI has spread into haunt flyers, props, projections and merchandise—citing Kennywood, The Darkness, AtmosFX, Knott's Berry Farm and Queen Mary Dark Harbor—and that this undercuts the originality and physical craft that make haunts distinctive, even as non-generative AI is used behind the scenes for prop timing and safety planning.

Will AI expose the rickety infrastructure of the internet?

In a TechCrunch Equity podcast discussion, the hosts examined a widespread PHP vulnerability that forced website owners to patch immediately or take sites offline, with Sean O'Kane calling it "a real reckoning moment" showing that at the bone level the internet is "held together with glue and dreams." The panel noted that widespread access to LLMs and AI agents will make finding such vulnerabilities easier, while the specific flaws were found by human researchers, and Kirsten Korosec raised concerns about link rot and larger risks to banks and data privacy.

Five weird details from Anthropic’s IPO filing

Anthropic’s S-1 filing discloses that CEO Dario Amodei received nearly $18 million in total compensation last year and President Daniela Amodei $16.4 million, plus millions spent on personal security and a private jet for Dario. The filing also lists unconventional risk factors, including potentially "catastrophic" AI harm and the possibility of AI systems possessing "forms of sentience," and details compute commitments such as roughly $3.1 billion per month to SpaceX for Nvidia GPUs, up to $120.5 billion by 2029. A "Founder LLC" will give the seven cofounders 50.1 percent of shareholder voting power on key matters, and Anthropic names only OpenAI and Google as direct competitors.

Sierra is on Google Cloud Marketplace

Sierra is now available on Google Cloud Marketplace, letting companies use existing Google Cloud commitments to build and deploy AI agents, with payment based on outcomes delivered rather than tokens consumed. Qualifying Marketplace purchases count toward Google Cloud commitments, with unified billing and Private Marketplace governance in the Google Cloud Console. Sierra says nearly 50% of the Fortune 50, 1 in 3 leading banks, and 5 of the 10 largest healthcare companies work with it.

Kevin Roose is AGI-pilled. Why aren’t you?

In this Decoder interview, Kevin Roose discusses leaving The New York Times with Casey Newton to launch the video-first podcast Machine Gods, and his new book The AGI Chronicles, a reported history of the frontier labs racing to build artificial general intelligence. He describes how the transformer gave companies a tool for a long-held dream, how labs differ in how "AGI-pilled" they are (with Anthropic most and Google least), and how belief in AGI drives both bet-the-farm compute spending and a struggle to focus on business fundamentals.

The focus on AI safety disasters ignores everyday harms

The article argues that the technology policy debate is dominated by catastrophic harms while the everyday damage of products—AI companions fostering dependence, chatbots writing students' work, engagement-driven feeds—goes largely unaddressed. It contends that companies promote narrow safety definitions because they are politically convenient and good for business, citing Google-backed state chatbot bills with broad carve-outs and social media's documented harms. The authors call for stronger measures, including requiring proof that AI improves learning before classroom adoption and banning companions designed to pretend to be conscious or profess love.

Google’s AI search changes upended online publishing

The article reports that Google's AI Overviews and AI Mode have reduced search traffic to online publishers, citing Similarweb data showing The New York Times' search traffic share falling from 44 percent to 35.5 percent over three years and DMG Media reporting click-through rates dropping by up to 89 percent between June and July 2025. Google disputes this, with Search head Liz Reid saying click volume remained "relatively stable," while publishers have filed lawsuits and leaned on social media, newsletters, and subscriptions; Google has since made sources more prominent and runs a News AI pilot with 400 publishers.

Ex-Google CEO Eric Schmidt calls OpenAI and Anthropic modern colonial trading companies

In a Foreign Affairs essay, historian Niall Ferguson, researcher Lisa Klaassen, and former Google CEO Eric Schmidt compare OpenAI and Anthropic to colonial-era East India Companies, citing a June case in which the US Commerce Department ordered Anthropic to cut off foreign nationals from its two most capable models. They argue model progress depends on energy, minerals, chips, and capital, and describe raw materials from the Congo and low-paid data workers in Kenya as "the plantation economics of the chatbot age." The authors outline an "imperial trilemma" in which defense, tech leadership, and a generous welfare state cannot all survive at once, and warn that a potential "Taiwanese chip crisis" remains the greatest danger.

The AI graveyard: a running list of projects and startups that didn’t make it

This roundup catalogs AI products, startups, and corporate initiatives that shut down, pivoted, or missed expectations, including Relay, Character.ai, OpenAI's Atlas browser and Sora, Apple's delayed Siri, Microsoft's Recall, Notion Mail, Humane AI Pin, Rabbit R1, Huxe, Yupp, and Figgs AI. It cites S&P Global Market Intelligence's figure that about 42% of AI initiatives are ultimately abandoned by their corporate parents, attributing failures to insufficient funding, technical challenges, competition, scaling difficulty, or weak demand.

AI makes junior patent attorneys instantly better but may quietly stunt their professional growth

A Google-funded study had patent attorneys draft claims with an unreleased Google Labs AI assistant called InFlow and then redline a flawed draft without AI, with blinded attorneys scoring results across five categories. AI-assisted drafting gains were much larger for juniors than seniors, but on the unaided redlining task only seniors retained an advantage while juniors showed wider score spread with more low and high ratings. The authors suggest baseline expertise may be needed to convert AI-assisted practice into durable skill, while noting limitations including small sample size and a three-month window.

Updated Google privacy policy says your Gmail might be used for advertising

Google updated its privacy policy on October 16, replacing the statement that it doesn't show personalized ads based on content from Drive, Gmail, or Photos with language that opens the door to using such data when shared with other Google services. The article links this to Personal Intelligence, released in early 2026, which lets users hand data from multiple apps to Google AI products.

Bringing foundational models to the front lines of TB screening

Google Research and Google for Health describe their path from a 2019 Radiology benchmark showing deep learning could match radiologists in detecting active pulmonary TB to prospective multi-site validation, CE MDR Class IIb certification via Nexus AI, and deployment in about 40 facilities across six countries, where over 90 clinicians have evaluated more than 25,000 chest radiographs. They also detail offline AI screening four kilometers underground at South Africa's Mponeng Gold Mine and open models (HAI-DEF, MedSigLIP, MedGemma, HeAR), including Indonesia's Ministry of Health fine-tuning MedGemma and MedSigLIP on domestic chest radiographs for a national TB program.

Now Google says it might use your Gmail and Google Photos data to target ads

Google updated its privacy policy on October 16 to add an exception allowing data from Drive, Gmail, or Google Photos to be used for personalized ads if users make that data available to other Google services supporting personalized ads, such as AI Mode and Search tools via Personal Intelligence. Advertisers don't get access to the content or personally identifying details, and Google says it won't target ads based on sensitive categories like race, sexual orientation, religion, or health. Users can disconnect apps from Search's Personal Intelligence features or disable Personalized Recommendations in the Search Services Personalization settings page.

Google Cloud now offers OpenAI models alongside Gemini and Claude, becoming the only major provider with all three

Google Cloud says it is now the only major cloud provider offering Gemini, Claude and OpenAI models on one platform, with three OpenAI models available from today: GPT-6 Astra for demanding tasks like coding and research, GPT-6.1 Sol as a cheaper alternative with similar performance, and GPT-6 Luna as a fast, cost-efficient option for everyday use. The models launch as a private preview for select enterprise customers with sign-ups open now, will also appear in Gemini for Business and Google Antigravity, and are billed through a single Google Cloud bill counting toward existing contracts, with Google stating customer data won't be used for training. The article notes a recurring tension at Google, since compute spent serving cloud customers strengthens its Gemini team's biggest rivals, a conflict it says reportedly pushed researcher Noam Shazeer back to OpenAI.

PHP Armageddon: OpenAI, Google’s Wiz find ancient holes, panicking the internet

The NSA warned that two critical vulnerabilities found in PHP, which powers roughly 70% of websites, allow attackers to infiltrate a server's file system or database, and urged sites that cannot be patched immediately to be taken offline. The flaws have existed in all PHP versions since version 5 (2004), and the recommendation is to update to PHP 8.5.12, since PHP 8.1 and older are no longer supported. OpenAI's Calif found one flaw using GPT-5.6 Sol under the "Patch the Planet" initiative, while Wiz used its Atlas agent with Gemini 4 Argon and GPT-5.6 Sol to find multiple vulnerabilities; both worked with PHP on patches before disclosure, and no exploits in the wild have been reported.

Featured coverage of this story: 《Hackers got a four-day head start on epic PHP2Shell vulnerability》

Google's Agent Compute Engine gives every Gemini agent its own hardware-isolated micro virtual machine

Google announced Agent Compute Engine, which gives each AI agent its own isolated microVM secured by its Titanium chip; it already powers Gemini and will open for preview in the coming months. Idle agents' VMs pause automatically to free machines for others, and shared memory between VMs reduces per-agent running costs; Google says it can fit ten times as many agents on a single server, and a 200,000-agent test showed suspend and resume in under 500 milliseconds. Google is also adding token tracking, model routing, and support for third-party identity providers like Ping Identity and SailPoint, extending to Cloud Run, GKE, and managed endpoints.

Beyond tree cover: mapping the world’s forest types

Google DeepMind and Google Research, with the World Resources Institute and IIASA, released Forest Typology (ForTy) 2020, a global 10-meter-resolution map classifying land into six FAO-based categories: primary forest, naturally regenerating forest, planted forest, plantation forest, tree crops and agroforestry, and other land. An accompanying early time series tracks annual changes from 2017 to 2025, including where natural forests were replaced by plantations or farms. Validated against more than 9,000 expert-reviewed sites, ForTy identified the correct forest type 90% of the time and distinguished forest from non-forest land 95% of the time, and the map and time series are freely available on Google Earth Engine under an open license.

[AINews] OpenAI’s Patch the Planet program is 1 of 2 parties to discover PHP2Shell vulnerabilities in core PHP affecting 70% of the web, using GPT-5.6 Sol; coordinated response over 2 months

Researchers disclosed two PHP-engine memory-corruption vulnerabilities, named PHP2Shell (CVE-2026-109618 and CVE-2026-109619), with reported pre-authentication RCE demonstrations against WordPress, Drupal and Joomla and Heartbleed-style memory disclosure. OpenAI says Calif researchers found the flaws using GPT-5.6 Sol under its Patch the Planet project, while secondary reporting says Wiz independently found the same bugs, and OpenAI describes roughly two months of coordinated remediation before disclosure. Cloudflare deployed WAF mitigations before the scheduled patch release, calling them a stopgap and directing operators to patch at 14:00 UTC.

OpenAI's GPT-5.6 Sol and Google's Gemini 4 Argon found critical PHP flaw affecting millions of websites

AI models from OpenAI and Google found a critical PHP vulnerability that could affect millions of websites worldwide, with GPT-5.6 Sol tracking down the flaw as part of OpenAI's Patch-the-Planet initiative. Security firm Wiz independently found the same flaws using its Wiz Atlas platform alongside Gemini 4 Argon and GPT-5.6 Sol, and the fix was coordinated over two months across five phases involving PHP developers, Wiz, Cloudflare, CISA and the White House. Wiz notes that large language models lower the barrier for attackers by automatically adjusting exploits across different PHP versions, configurations and memory layouts.

OpenAI's latest AI models are coming to Google Cloud and Antigravity

OpenAI and Google have reached an arrangement to bring OpenAI's frontier models to Google Cloud services, with the latest models appearing in Google's Model Garden in the coming weeks and GPT models soon arriving in Antigravity, Google's agent-powered coding tool. The full suite of current GPT 6 and 6.1 models—Astra, Sol, and Luna—will launch on Google Cloud and run entirely on Google's infrastructure, with transactions handled via the Google Cloud Marketplace, while Microsoft remains OpenAI's primary cloud partner. Google says it is now the only large cloud provider offering access to all three leading closed LLMs.

Empowering frontline maternal care with AI-assisted ultrasound

Google researchers evaluated an AI model that estimates gestational age from standardized "blind sweep" ultrasounds performed by novice operators, reporting a mean absolute error of 4.18 days versus 4.48 days for expert sonographers across cohorts in Chicago and Nairobi. The model, minimally tuned on 120 Chicago participants and tested with no Nairobi data, achieved MAEs of 4.10 and 4.27 days respectively, as published in JAMA Network Open.

The $15 billion ad-powered AI startup your doctor may already be using

OpenEvidence, a $15 billion AI startup, is being adopted by doctors and is backed by investors including Thrive Capital and the Mayo Clinic, with founder Nadler saying the end goal is literature-based drug discovery. Anthropic's Claude Science creator Alexander Tarashansky has joined the company, which faces competition from OpenAI and Anthropic in healthcare AI. Studies have shown mixed results, with a Mayo Clinic study finding accurate evidence-based recommendations in five sampled cases while a Nature paper found it underperformed Gemini and GPT on clinical benchmarks.

OpenAI models are coming to Google Cloud

OpenAI and Google Cloud are bringing frontier models and Codex workflows to Gemini's Model Garden, available through Google Cloud Marketplace.

Google Cloud and NVIDIA Announce General Availability of NVIDIA Vera Rubin Infrastructure

Google Cloud and NVIDIA announced general availability of NVIDIA Vera Rubin-based A5X instances next month, with planned expansion to Europe, combining Vera Rubin NVL72, ConnectX-9 SuperNICs, Google Cloud Virgo Network and fourth-generation liquid cooling for training, inference and large-scale reinforcement learning. Google Cloud plans to scale the infrastructure to as many as 960,000 Rubin GPUs across multiple sites, and Ineffable Intelligence, founded by AlphaGo creator David Silver, was the first customer to access A5X. Google Cloud also said it will be among the first cloud providers to offer NVIDIA Confidential Computing at rack scale on bare metal instances such as A4X Max powered by GB300 NVL72, and is making Confidential Computing generally available on G4 VMs powered by RTX PRO 6000 Blackwell Server Edition GPUs.

NVIDIA Confidential Computing Expands, Enabling Frontier Model Builders to Securely Scale Across Global Infrastructure

NVIDIA is expanding its Confidential Computing portfolio with Confidential Bare Metal, a deployment option that lets frontier model builders run sensitive workloads on dedicated third-party infrastructure while retaining control of their models and data. The offering joins Confidential Containers and Confidential Virtual Machines in a converged security architecture, with support extending to NVIDIA Grace Blackwell NVL72, HGX Rubin NVL8 and DGX Rubin NVL8 systems. Cohere plans to integrate Confidential Bare Metal into Cohere Model Vault, and Google Cloud is extending support to A4X Max instances powered by NVIDIA GB300 NVL72 systems.

Gemini's Personal Intelligence is coming to cars

Google is rolling out its Personal Intelligence feature for Gemini to Android Auto starting today, with vehicles that have Google built-in to follow in the next few months. The optional feature lets Gemini draw on data from apps like Gmail and Calendar to provide context for its answers.

Hugging Face ❤️ TorchTPU: TPUs, Natively

TorchTPU adds TPU as a native PyTorch backend, letting Transformers, Diffusers and Kernels run on TPU by sending models to "tpu" instead of going through torch_xla or JAX, and Optimum TPU is no longer required. The post shows loading a model with device_map="tpu", running Diffusers pipelines with pipe.to("tpu") plus optional torch.compile, and using Pallas kernels from the Kernels Hub, with reported speedups of 21.5× on Qwen3-30B-A3B and 12.8× on Gemma 4 26B-A4B at batch size 64. It also reports that 96.5% of tests run on TPU pass, with 34 issues filed on the TorchTPU repo and 19 already fixed.

Grounding AI agents in biological reality: Building blocks for autonomous wet labs

Google researchers describe three projects aimed at connecting AI agents to real wet-lab experimentation: the VERID framework, a semantic digital twin of a lab workcell that tracks 3D state, runs fast virtual dry runs, blocks unsafe commands and logs synchronized video and actions; closed-loop aptamer design over three design-test cycles that raised on-target hit rates to 33.5% for myoglobin and 42.1% for α-thrombin; and agent-guided epitope excision for de novo binder design against FAP, which accelerated each folding cycle more than eightfold and, in a human–agent comparison at equal compute, nearly doubled the in-silico hit rate of a scientist working alone.

Accelerating the search for antimicrobial peptides with Google Antigravity

Google describes how its agentic development platform, Google Antigravity, lets biologists discover, structurally evaluate and prioritize antimicrobial peptide candidates in a single session, using ProtNLM to scan millions of uncharacterized UniProt proteins. A technical walkthrough shows a researcher and agent identifying a novel antimicrobial peptide candidate with predicted activity against respiratory tract infection pathogens, now undergoing wet-lab validation. The post also introduces the Biomolecular Structure Viewer, a 3D visualization tool embedded in Antigravity that shares visual state between researcher and agent.

Analyzing technical documents with Deep Review

Google announced the public release of Deep Review, an agentic AI system that provides feedback and technical verification on complex documents, initially for computer science papers and now extended to legal, finance, and other domains. It evolved from the Paper Assistant Tool, which was piloted with STOC 2026, ICML 2026, NeurIPS 2026, and ICLR 2027, offering opt-in pre-submission feedback to authors of more than 16,000 manuscripts. Every user gets two complimentary reviews per week, with higher limits via a Gemini API key, and uploaded documents are not used to train Google models.

Putting Earth AI to work: Geospatial agents for our planet's biggest challenges

Google shares a technical report on its experimental Geospatial Reasoning agent, which connects Gemini to Earth AI foundation models and planet-scale data, and reports evaluations across four benchmarks, including two newly released ones (GeoKTools and GeoExpertQueries). The post describes early partner testing with organizations including WHO AFRO, People in Need, GiveDirectly, the Milken Institute and WPP, and announces expanded early access via Ask Google Earth and an experimental agent-to-agent API.

Research@ 2026: 10 ways we're amplifying human ingenuity

At its Research@ event in Mountain View, Google Research outlined 10 updates, including expanded early access to Google Earth AI's experimental geospatial capabilities, a multi-agent orchestrator for reproducing prior methods, and public access to its Deep Review verification system. Other highlights include the Synaptics Astra SR200 Series chip with Google's co-designed Coral NPU, upcoming integration of TimesFM and TabFM into Gemini for business, and a Lancet study in which 98 patients consulted AMIE ahead of urgent care visits. Google.org is also providing $10 million in funding for crisis resilience and public health work.

Google DeepMind and Singapore Government collaborate to build fine-tuned AI model for scam detection

Google DeepMind and GovTech Singapore fine-tuned Google's lightweight Gemma model on local scam conversations to create a privacy-preserving, on-device scam detection model that processes conversation data directly on the device. The model uses a two-stage pipeline—a lightweight classifier screening inbound messages, followed by in-context analysis with the fine-tuned Gemma model—to trigger real-time warnings, and was developed within GovTech's GCP environment using anonymised datasets without private or personally identifiable information. Presented at Singapore International Cyber Week (SICW 2026), the collaboration is described as a model for messaging platforms balancing user protection with end-to-end encryption.